Process Engineer, AI/Data Science

What you'll do

• Design, develop, and program methods to analyze unstructured data into actionable insights.
• Conduct lab experiments on semiconductor products to generate data for analysis.
• Develop advanced test vehicles to support experimental research and evaluation.
• Create predictive models from early experimentation to identify physical mechanisms.
• Perform systematic root cause analysis to solve complex engineering problems.
• Compile and evaluate test data to determine limits and variables for process specifications.
• Develop algorithms and automated processes to analyze complex datasets from disparate sources.
• Communicate technical results clearly to audiences with varying levels of expertise.

What we're looking for

• Ph.D. or Master's degree in chemical engineering, materials science, chemistry, or engineering physics.
• Master's degree in Data Science, Statistics, Computer Science, Engineering, or Applied Mathematics is acceptable if the candidate has experience applying data science to engineering problems.
• Minimum of 0-2 years work experience.
• Demonstrated expertise in data science, machine learning, artificial intelligence, or advanced analytics.
• Experience in experimental laboratory settings to refine data collection and analysis.
• Knowledge of statistical analysis and modeling including Statistical Process Control (SPC) and Design of Experiments (DOE) (preferred).
• Expertise applying AI and machine learning methodologies to physical systems (preferred).
• Experience in semiconductor or chemistry laboratories (preferred).